AWESOME: a database of SNPs that affect protein post-translational modifications

Area of Science:

• Genomics
• Proteomics
• Bioinformatics

Background:

• Protein post-translational modifications (PTMs) are crucial biological processes.
• Alterations in PTMs, often due to genetic variations like single nucleotide polymorphisms (SNPs), are linked to disease risk.
• Missense SNPs are increasingly recognized for their role in complex disease susceptibility.

Purpose of the Study:

• To develop a comprehensive database and analysis tool for evaluating the impact of SNPs on PTMs.
• To provide a platform for systematically assessing SNP-induced PTM changes and their functional consequences.
• To facilitate the identification of pathogenic PTM-related SNPs and potential therapeutic targets.

Main Methods:

• Construction of the AWESOME (A Website Exhibits SNP On Modification Event) database.
• Integration of 20 PTM prediction tools for comprehensive SNP analysis.
• Development of a scoring system to evaluate and compare PTM prediction tool performance.

Main Results:

• AWESOME provides an interactive web-based tool for evaluating SNP effects on various PTMs.
• The database allows users to search for SNPs, genes, or positions and filter by modification type or prediction method.
• A scoring system aids in interpreting results and comparing the efficacy of different prediction tools.

Conclusions:

• AWESOME offers a convenient resource for detecting PTM-related SNPs.
• The database can help identify potential pathogenic factors and therapeutic targets associated with SNP-induced PTM alterations.
• This tool supports research into the functional mechanisms linking genetic variations to disease.